Cardiac Implantable Electronic Devices with a Defibrillator Component and All-Cause Mortality in Left Ventricular Assist Device Carriers: Results from the PCHF-VAD Registry
Bibliographic record
Abstract
AIMS: To compare characteristics of left ventricular assist device (LVAD) recipients receiving a cardiac implantable electronic device (CIED) with a defibrillator component (implantable cardioverter-defibrillator and cardiac resynchronization therapy with defibrillation, CIED-D) vs. those without one, and to assess whether carrying such a device contiguously with an LVAD is associated with outcomes. METHODS AND RESULTS: Overall, 448 patients were analysed (mean age 52 ± 13 years, 82% male) in the multicentre European PCHF-VAD registry. To account for all active CIED-Ds during ongoing LVAD treatment, outcome analyses were performed by a time-varying analysis with active CIED-D status post-LVAD as the time-varying covariate. At the time of LVAD implantation, 235 patients (52%) had an active CIED-D. Median time on LVAD support was 1.1 years (interquartile range 0.5-2.0 years). A reduction of 36% in the risk of all-cause mortality was observed in patients with an active CIED-D [hazard ratio (HR) 0.64, 95% confidence interval (CI) 0.46-0.91; P = 0.012), increasing to 41% after adjustment for baseline covariates (HR 0.59, 95% CI 0.40-0.87; P = 0.008) and 39% after propensity score adjustment (HR 0.61, 95% CI 0.39-0.94; P = 0.027). Other than CIED-D, age, LVAD implant as redo surgery, number of ventricular arrhythmia episodes and use of vasopressors pre-LVAD were remaining significant risk factors of all-cause mortality. Incident ventricular arrhythmias post-LVAD portended a 2.4-fold and 2.6-fold increased risk of all-cause and cardiovascular death, respectively; carrying an active CIED-D remained associated with a 47% and 43% reduction in these events, respectively. CONCLUSIONS: In an analysis accounting for all active CIED-Ds, including those implanted during LVAD support, carrying such a device was associated with significantly better survival during LVAD support.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".